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    Data and Machine Learning Engineer - Los Angeles, United States - First Resonance

    First Resonance
    First Resonance Los Angeles, United States

    3 weeks ago

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    Description

    We are looking for a data ninja and machine learning guru to join our mission of revolutionizing the ION Factory OS for next-gen hardware creators. As a full-time addition at our lively Los Angeles, CA HQ (Downtown), you'll play a crucial role in our dynamic data team.

    Fired up to support eVTOLs, rockets, robots, and autonomous vehicles makers? Our data team is all about backing companies tackling humanity's boldest challenges. Join our diverse squad, renowned for quick learning, sharp thinking, and agile execution.

    While spontaneous ping pong duels might occur, our primary focus is on empowering ION customers with cutting-edge data infrastructure. Ready to make an impact on hardware and Industry 4.0? Let's dive in

    Job Overview:

    As a Data/ML Engineer, you will be pivotal in designing, building, and maintaining our data processing frameworks and machine learning systems. You will work closely with the engineering team to solve complex problems and deliver scalable, robust, and efficient data-driven solutions to meet business needs.

    Responsibilities:

    • Design, implement, and launch new and exciting machine learning features into production.
    • Collaborate with team members to understand data requirements and implement systems for large-scale data analysis and prediction.
    • Maintain and enhance our data infrastructure to support the collection, storage, processing, and analysis of large data sets.
    • Develop statistical models and generative AI solutions.
    • Implement best practices in data governance and security.
    • Stay current with industry trends and evaluate new technologies for on-going improvements.
    Required Qualifications:
    • Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field.
    • 5+ years of experience in data engineering or machine learning roles.
    • Strong proficiency in programming languages such as Python, Rust, Scala, or JavaScript.
    • Experience with big data technologies such as Hadoop, Spark, and Kafka.
    • Deep understanding of machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn, Pandas, XGBoost, NumPy).
    • Solid experience with SQL and NoSQL databases.
    • Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
    • Excellent problem-solving skills and ability to work under tight deadlines.
    What kind of candidates we are NOT looking for:
    • Researchers specialized in machine learning/generative AI/statistical modeling
    • Big Data experts who solely focus on building data pipelines and data management solutions.
    • Engineers looking to jumpstart their careers in AI/ML/Data.
    Desirable Skills:
    • Experience with cloud platforms (AWS, Azure, Google Cloud).
    • Familiarity with Docker, Kubernetes, and CI/CD pipelines.
    • Publications or presentations in recognized Machine Learning and Data Engineering communities.
    Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Certain roles may be eligible for incentive compensation, equity and benefits.

    Pay Range

    $130,000-$170,000 USD

    First Resonance accelerates the speed and reliability of hardware development for companies manufacturing the next generation of hardware products. This includes electric airplanes, autonomous vehicles, robotics, and more. We are a group of software, hardware, and manufacturing engineers that are bringing the best of modern UX and data science to an industry that has been overly rigid in its innovation. We are removing the barriers preventing radical advancement by providing tools to manufacturing engineers and operators to move information more freely, collaborate with their teams more easily, and use the power of data to predict problems and provide insights that result in better hardware quality and delivery.
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